& Case Studies
200 hours Elearning
Practice Datasets & Case Studies
Learn Anywhere Anytime
Webinars by Industry Experts
Certification by Kaalp
Students from any discipline who are looking for better opportunity in Data Science or Analytics domain
Research scholars, academicians and scientists who wish to use Data Science applications in their respective areas of work & projects.
Corporate business professionals who wishes to learn data science applications to manage & run analytics processes
IT enabled Services executives ,database developers,business analysts, business intelligence and analytics who wish to learn Data science implementations.
Any previous knowledge of programming skill would suffice. Familiarity with any other packaged software or spreadsheet would be of help.
This chapter introduces to the statistical techniques that can be used with Excel like descriptive statistics, test of hypothesis & relationship between variables.
This chapter describes the various built-in functions & generators
This topic covers simple & advanced regular expression to handle string data
This chapter provides various summary statistics like mean, median & mode with helps in data compression
In this chapter you will learn high level overview of the important libraries used in Data Science
This chapter broadly describes various data munging & wrangling techniques using Pandas library
This chapter introduces you to different Numpy libraries useful for handling quantitative data
The chapter discusses the different techniques to model historical time series data using Python.
Know how Open database connectivity is used in R
Reading data from files & different sources
The below topics describes various visualization techniques to show the relationship of the variables
The below mentioned topics cover unsupervised machine learning techniques
Learn how to build robust machine learning models when data is non linear
In this chapter learn easy to use interactive web based dashboards with R